Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression
Reexamination Certificate
1998-10-05
2001-06-26
Teska, Kevin J. (Department: 2123)
Data processing: structural design, modeling, simulation, and em
Modeling by mathematical expression
C701S006000, C701S014000, C702S150000, C700S089000
Reexamination Certificate
active
06253166
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention The present invention relates in general to flow instrumentation and more particularly to an airdata estimation and evaluation system and method for estimating and evaluating airdata from noninstrusive surface pressure measurements.
2. Background Art
Airdata are critical information for any type of flight vehicle. Airdata are those parameters, characteristics, properties and quantities derived from the air surrounding the flight vehicle. Accurate airdata are absolutely necessary for many purposes and applications and help to ensure efficient and safe flight.
For example, a pilot cannot safely fly an aircraft without knowing its airspeed and pressure altitude. In civil aviation, air traffic controllers determine the separation distances between aircraft based on accurate knowledge of the aircraft's pressure altitude. If the airdata is inaccurate, the aircraft's true pressure altitude may differ greatly from its reported pressure altitude, and disaster may result.
Numerous other aircraft systems also need accurate airdata. Autopilot, engine controls, cockpit and cabin environmental controls, weapons delivery, navigation and air traffic control are just a few examples of aircraft systems that depend on accurate airdata.
Airdata are most accurate when the undisturbed air away from the flight vehicle is measured. This is because the presence of the flight vehicle in the air can cause measurement errors. Moreover, as the velocity of the flight vehicle increases, compressibility and shock waves further disrupt the surrounding air.
Traditionally, in order to mitigate these errors, airdata measurements have been performed using booms that extend outward from the flight vehicle and measure the undisturbed air. Typically, these intrusive booms contain a pressure-measuring instrument that operates by stagnating the freestream flow and measuring the difference between static and impact pressure. These booms are usually located at the nose of the flight vehicle. Although these booms are excellent at making steady measurements at low-to-moderate angles of attack, the booms are sensitive to vibration, alignment error and are easily damaged in flight or on the ground.
There are also several applications where an intrusive boom is undesirable. For example, on hypersonic aircraft an intrusive boom may either be torn off by the forces generated in flight or melted by the high temperatures involved in high-speed flight. On stealth aircraft, where a minimum radar cross section is required, an intrusive boom is undesirable because it makes the aircraft highly visible to radar. Therefore, intrusive booms are generally unsuitable for airdata measurements in more advanced types of flight vehicles.
One technique developed to overcome these difficulties with the conventional intrusive boom was a flush airdata sensing (FADS) system. Unlike the intrusive boom that directly measures airdata from the freestream air, the FADS system infers airdata from nonintrusive surface pressure measurements.
The fundamental concept of the FADS system is that it does not require probing of the freestream flow in order to compute airdata. Instead, airdata can be estimated and evaluated from flush surface pressure measurements. These pressure measurements are then related to airdata using aerodynamic model equations that mathematically describe the flow. Solving the aerodynamic model equations mathematically extracts the airdata given the surface pressure measurements.
One early use of a FADS system was in the 1960s by the X-15 high-altitude, hypersonic aircraft. The X-15 FADS system used a hemispherical nose that was actively steered into the local relative wind to make airdata measurements. One drawback to this system, however, was that the actively steered nose was an extremely complicated mechanical design. Consequently, the steered-nose FADS system was abandoned with the termination of the X-15 program.
A modern FADS system was developed as an experiment on the space shuttle. The shuttle entry airdata system (SEADS) was a “ride-along” experiment aboard the shuttle but never was used to actually provide airdata to the shuttle pilot. The SEADS used a matrix of fixed static-pressure measurements and required no mechanical steering of the nose.
The problem, however, with both of these systems is that both are quite inaccurate. This is because the two systems merely focused on the feasibility of the FADS concept and made no attempt to derive algorithms for more accurate estimation and evaluation of airdata from the surface pressure measurements.
The next advance in FADS technology was a real-time, high angle-of-attack FADS (HI-FADS) system. The HI-FADS design, as with the earlier X-15 FADS system and the SEADS, used a matrix of flush static-pressure orifices arranged on the nose of the flight vehicle. Moreover, the HI-FADS system did attempt to derive algorithms for estimating and evaluating airdata from surface pressure measurements.
One problem, however, with the HI-FADS design is the complexity of the algorithm and the associated increased costs. In particular, the system incorporates all surface pressure measurements simultaneously into an overdetermined estimation algorithm. Furthermore, airdata parameters are inferred using nonlinear regression methods. However, the use of these nonlinear regression cause the estimation algorithm to be highly unstable and complex. In addition, the cost of maintaining the software implementing this algorithm is quite high.
In order to solve these aforementioned problems with these prior art FADS systems, the present invention was developed to provide a reliable and accurate FADS system for use in the X-33 flight vehicle program. The X-33 is 53-percent scale model of the Single Stage to Orbit (SSTO) Reusable Launch Vehicle (RLV) rocket system. The primary goal of the SSTO program is to radically reduce the cost of access to space, and the X-33 is a demonstrator of this advanced technology. The X-33 is designed to achieve a peak altitude near 300,000 feet and speeds of greater than Mach 12. After atmospheric re-entry, the X-33 returns to Earth in an unpowered horizontal landing.
Because the X-33 will perform an unpowered landing (i.e. there is only a single landing attempt), highly accurate determination of the airdata such as dynamic pressure, angle-of-attack, and surface winds is critical to insure that the target runway can be reached under a wide variety of atmospheric conditions. Furthermore, direct feedback of angle-of-attack and angle-of-sideslip may reduce the gust-load on the vehicle airframe during the ascent phase of the flight.
The determination was made early in the X-33 program that the full airdata state including Mach number, angle-of-attack, angle-of-sideslip, dynamic pressure, airspeed and altitude would be a critical requirement for both the RLV and the X-33 and that existing FADS algorithms could not adequately fulfill this requirement.
Specifically, there are several problems with existing FADS algorithms. One problem is that the nonlinear regression method used in the estimation algorithm tends to be highly unstable. In fact, the software implementing this algorithm requires numerous special software patches in an attempt to maintain stability.
This highly unstable algorithm leads to the problem of complexity. Specifically, the special software patches required to make the algorithm stable also require a complex maze of software designed to maintain stability. Moreover, the cost of establishing and maintaining this software is extremely high.
Another problem with existing FADS systems is that the unstable estimation algorithm can lead to numerous reliability problems. This, in turn, has detrimental consequences for the flight vehicle that relies on accurate airdata.
Therefore, what is needed is a FADS system that has a highly stable estimation and evaluation algorithm that can easily be implemented with a minimum of cost and maintenance. Moreover, what is further needed is a FADS system having an estima
Cobleigh Brent R.
Haering, Jr. Edward A.
Whitmore Stephen A.
Frejd Russell W.
Kusmiss John H.
Teska Kevin J.
The United States of America as represented by the Administrator
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